Introduction to Spark

Resilient Distributed Datasets

Advanced RDDs: Pair Resilient Distributed Datasets

PageRank: Ranking Search Results

Spark SQL

MLlib in Spark: Build a recommendations engine

9

Spark Streaming

10

Graph Libraries

11

Scala Language Primer

12

Supplementary Installs

You, This Course and Us
Installing Scala and Hello World
Downloadable Files

What does Donald Rumsfeld have to do with data analysis?
Why is Spark so cool?
An introduction to RDDs - Resilient Distributed Datasets
Built-in libraries for Spark
Installing Spark
The Spark Shell
See it in Action : Munging Airlines Data with Spark
Transformations and Actions
Downloadable Files

RDD Characteristics: Partitions and Immutability
RDD Characteristics: Lineage, RDDs know where they came from
What can you do with RDDs?
Create your first RDD from a file
Average distance travelled by a flight using map() and reduce() operations
Get delayed flights using filter(), cache data using persist()
Average flight delay in one-step using aggregate()
Frequency histogram of delays using countByValue()
Downloadable Files

Special Transformations and Actions
Average delay per airport, use reduceByKey(), mapValues() and join()
Average delay per airport in one step using combineByKey()
Get the top airports by delay using sortBy()
Lookup airport descriptions using lookup(), collectAsMap(), broadcast()
Downloadable Files

Get information from individual processing nodes using accumulators
Long running programs using spark-submit
Spark-Submit with Scala - A demo
Behind the scenes: What happens when a Spark script runs?
Running MapReduce operations
Downloadable Files

What is PageRank?
The PageRank algorithm
Implement PageRank in Spark
Join optimization in PageRank using Custom Partitioning
Downloadable Files

Scala - A "better Java"?
How do Classes work in Scala?
Classes in Scala - continued
Functions are different from Methods
Collections in Scala
Map, Flatmap - The Functional way of looping
First Class Functions revisited
Partially Applied Functions
Closures
Currying
Downloadable Files

Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings.

Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX.

Write code in Scala REPL environments and build Scala applications with an IDE.

About the course

This course is taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. Get your data to fly using Spark for analytics, machine learning and data science.

Get your data to fly using Spark and Scala for analytics, machine learning and data science

Let’s parse that!

What's Spark? If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.

Scala: Scala is a general purpose programming language - like Java or C++. It's functional programming nature and the availability of a REPL environment make it particularly suited for a distributed computing framework like Spark.

Analytics: Using Spark and Scala you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.

Machine Learning and Data Science: Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets.